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ML courses often start with linear regression, and if you build up complicated polynomials to find a nonintuitive model of your problem, I would definitely cons
by yessql 10y ago
ML courses often start with linear regression, and if you build up complicated polynomials to find a nonintuitive model of your problem, I would definitely consider that machine learning.
- sidlls 10y agoI wouldn't. I'd call it "basic computational statistics." But I think I might be in the minority on that.
- Bartweiss 10y agoI've always thought of regressions, even high-order ones, as just a statistical tool. They're present at the start of ML courses, sure, but as a tool used in ML techniques or a good alternative to them. It looks like that's not the standard view, though.
- LolWolf 10y agoThe whole deal seems weird to me. Neural networks are just functional approximators, so why isn't a linear regressor of k-th order (e.g. Taylor expansion up to k-th order) also considered "ML"? What's the distinction here?